Abstract: A method, system and software for determining a final staffing schedule by scheduling a plurality of staffing resource units (SRUs) into a plurality of shifts. The method includes the following steps (not necessarily in the following order except as explicitly indicated): (i) determining an initial staffing schedule; (ii) iteratively-adding SRUs to the staffing schedule until it is determined that the staffing schedule meets a feasibility condition; (iii) iteratively-subtracting SRUs from the staffing schedule until it is determined that the staffing schedule meets at least one improper condition; and (iv) subsequent to the subtracting step, adding a single SRU to the staffing schedule to yield the final staffing schedule.

Abstract: A method, system and software for determining a final staffing schedule in a ticketing system by scheduling a plurality of staffing resource units (SRUs) of multiple classes into one or more shift(s). The method includes finding a simulated staffing schedule for some sub-set of class(es), where the sub-set of class(es) is: (i) less than the total number of classes; and (ii) can accomplish all tasks that may come in during the shift(s) being scheduled. The schedule for the sub-set of classes is then converted into a schedule including SRUs of every class based on historical data relating to historical proportions between SRUs of various classes and/or incoming tasks of various types.

Abstract: A method, system and software for determining a final staffing schedule in a ticketing system by scheduling a plurality of staffing resource units (SRUs) of multiple classes into one or more shift(s). The method includes finding a simulated staffing schedule for some sub-set of class(es), where the sub-set of class(es) is: (i) less than the total number of classes; and (ii) can accomplish all tasks that may come in during the shift(s) being scheduled. The schedule for the sub-set of classes is then converted into a schedule including SRUs of every class based on historical data relating to historical proportions between SRUs of various classes and/or incoming tasks of various types.

Abstract: A method, system and software for determining a final staffing schedule by scheduling a plurality of staffing resource units (SRUs) into a plurality of shifts. The method includes the following steps (not necessarily in the following order except as explicitly indicated): (i) determining an initial staffing schedule; (ii) iteratively-adding SRUs to the staffing schedule until it is determined that the staffing schedule meets a feasibility condition; (iii) iteratively-subtracting SRUs from the staffing schedule until it is determined that the staffing schedule meets at least one improper condition; and (iv) subsequent to the subtracting step, adding a single SRU to the staffing schedule to yield the final staffing schedule.

Abstract: Under the present invention, a GUI is provided that allows an assembly line to be both graphically and dynamically configured. In general, the GUI allows a designer or the like to “graphically” configure: a hierarchy of categories representing the assembly line; the process points along the assembly line; the different events that can be triggered at the process points; the actions that are taken in response to the events; the processes (sequences of actions) for the events; and the input parameters for the events and the actions. In a typical embodiment, the GUI is maintained on a system that is separate from the central computer controlling the assembly line. This not only allows the assembly line to be configured remotely, but also without ceasing operation of the line.

Abstract: The present invention provides a method, system, and computer program product for providing quality of service guarantees at the application level for clients of application servers. The method includes: receiving a request for a transaction of type k; calculating a throughput rate ?i of each type of transaction i, 1?i?n, in response to the request for the transaction of type k; calculating an average residual time Ri of each type of transaction i, 1?i?n; calculating an average residual time R of a transaction in service; calculating an average waiting time Wk of a transaction of type k; comparing the average waiting time Wk of a transaction of type k to a required average waiting time W{tilde over (k)} of a transaction of type k; and selectively accepting the request for the transaction of type k, based on a result of the comparing step.

Abstract: In the implementation of a production process, event data corresponding to a parent event that has triggered an executable business process that has failed is logged. The event data is displayed to a user. Responsive to input from the user, a child event based on the event data is generated, and the child event is submitted to a process engine to initiate re-execution of the executable business process in accordance with the child event.

Abstract: A method and apparatus for maximizing a transfer of data to a target. A set of packets using the first packet size and the second packet size is sent to the target to form a set of transferred packets. Round trip times and service times are identified for the set of transferred packets. Optimal packet size is selected using the round trip times and service times for the set of packets, wherein the optimal packet size is used in transferring the data to the target.

Abstract: A method and apparatus in a distributed data processing system for handling requests. The processing of each request received at a server system is monitored, wherein the server system includes a plurality of servers. An average work load size is estimated for the plurality of servers based on previous actual work load information in response to completion of processing of a request. A most recent value of the average work load size is assigned for the plurality of servers to each request arriving at the server system. The request is forwarded to a server within the plurality of servers having a lowest estimated amount of work to process.

Abstract: A method and apparatus in a distributed data processing system for handling requests. Processing of requests received at a server system is monitored, wherein the server system includes a plurality of servers. A work load is estimated at each of the plurality of servers. The request is forwarded to a server within the plurality of servers having an estimated smallest work load.

Abstract: The idle capacity of a packet network channel is dynamically estimated by transmitting only a single window of test packets at whatever window size is presently in use on the channel and by measuring the time intervals between acknowledgments (the inter-acknowledgment time) of adjacent packets. This value is used, for example, to dynamically allocate the idle bandwidth to applications. Preferably, an average value for the inter-acknowledgment time interval is calculated from all of the acknowledgment intervals associated with the window of packets. The idle capacity of the channel is then calculated from the formula C=1/IAvg, where C is the idle capacity in packets per second and IAvg is the average acknowledgment time between packets. Additionally, the same parameters that are collected to calculate the idle capacity are used to calculate the optimal window size, also on a dynamic basis.

Abstract: A data structure, which includes a plurality of sub-data structures, is created. The sub-data structures are ordered based on ranges of key masks associated with the sub-data structures. In particular, in one example, the sub-data structures are linked in a list in ascending order of key mask ranges, thus, creating an ordered list of sub-data structures. The ordered data structure can be modified by adding new nodes to existing sub-data structures or by adding new sub-data structures. Further, nodes or sub-data structures can be removed from the ordered data structure. The data structure can also be searched in order to collect target records associated with requested keys of the data structure.